Many prior art systems exist for detecting the presence of particles or size of particles in a fluid, such as a supply of potable water. For example, U.S. Pat. No. 5,438,408 entitled Measuring Device and Method for the Determination of Particle Size Distributions by Scattered Light Measurements discloses the use of a charge coupled device (CCD) camera. U.S. Pat. No. 6,061,130 entitled Apparatus for Determining the Particle Size Distribution of a Mixture discloses an apparatus that includes a CCD matrix. By identifying particles by predetermined parameters, such as diameter or cross-sectional area, such systems can ascertain the presence or absence of unwanted harmful bacteria in a water sample which are known to be within a predetermined range of diameters.
Some of these systems have also been known to be useful in analyzing other fluids such as blood and blood products. Typically, identifying particle populations in accordance with some parameter, for instance particle size or particle cross-section, allows a parameter distribution to be ascertained. In a water supply the goal may be to determine the number of particles of various sizes that are present in a representative sample.
Detection systems most often employ the use of computers or powerful processor-based systems coupled to one or more CCD or pixel arrays of detecting elements, which detect the presence of one or more particles projected upon a portion of the array of charge coupled elements. Most often thousands of frames of information are collected. Within a single frame more than a single particle may be detected; therefore, the software is programmed to find clusters of pixels, indicating the presence of a particle. Some software can determine instances where portions of particles overlap and determine the size of each particle.
In each successive frame, images of the particles contained within an optical sampling volume are projected onto the pixel array. These images of the particles are randomly distributed on the array depending on the positions of the particles in the sampling volume. In order to determine the value of a parameter of the particle, for example the cross-sectional area of a particle, the number of pixels in the particle image corresponding to that parameter covered, wholly or partially, is counted and a scaling factor is applied. Subsequently, a table is compiled of the number of counts corresponding to each pixel total as the images in each frame are analyzed. For example 90 pixels: 350 counts, implies that there are 350 instances of 90 pixels being at least partially covered by a particle, or stated differently, in the total number of frames analyzed, there are 350 instances of 90 detectors within the array sensing the presence of at least a portion of a particle; correspondingly, 91 pixels: 410 counts, indicates 91 detectors within the array sensed the presence of at least a particle in 410 separate instances. In order to produce the parameter distribution information, the parameter value corresponding to each pixel total must be determined. When the number of pixels is large, a simple scaling factor, which depends only on the pixel size and the magnification, gives accurate results. However when the number of pixels is small, that is, when only very few detectors sense the presence of at least a portion of a particle, this scaling factor becomes increasingly uncertain because of the image location error. Image location error results from the fact that the pixel total measured for a particular value of a particle image depends on the location of the image with respect to the pixel grid. This can be understood more clearly with reference to FIG. 1, where two particles P1 and P2 having a same cross-sectional area are shown superimposed over a pixel array. If the threshold of the array is set to its most sensitive, any partial coverage of an array element or pixel by a portion of a particle will trigger that array element to detect the presence of a particle. Particle P1 on the left of the array happens to be positioned such that it at least partially covers 9 pixels. Particle P2 on the other hand, being the same size as particle P1 at least partially covers or triggers 16 pixels at a different location on the CCD detector array. Of course, whether a partially covered pixel triggers an array element depends upon the threshold setting.
If a particle image is very large compared to the size of a pixel, for example covering 200 pixels, the variation in pixel total with location will be small, and will likely only vary a few percent with location. However the variation in pixel total is very large and in the neighborhood of 50% in the example described heretofore, where a same pixel is measured to be 16 pixels in cross-section in one instance and 9 pixels in cross section in another instance.
For in-line operation or, in applications where a large number of samples must be analyzed, it is desirable that measurements be made in the shortest possible time. For example it would be desirable to analyze a sample in several minutes and not in several hours. Furthermore, it is desirable that a single measurement at a single magnification provides information, i.e. the number of particles in each of a specified range of equivalent diameters for the particles having the largest possible range of sizes. To ensure that the image location error is small, a sufficiently high magnification may be selected so that the images of the smallest particles occupy a sufficient number of pixels. Approximately 200 are required to reduce equivalent diameter measurement errors to ±6%. However, as magnification is increased, the optical sampling volume becomes smaller. By way of example: the time required to analyze a typical sample of 1 cc, using a magnification such that a 2.5 micron particle occupies two hundred 7.5×7.5 micron pixels, is approximately 5 hours. Furthermore as magnification is increased, the size of the largest particle, which may be imaged without incurring a significant probability that its image will overlap with the edge of the pixel array, is reduced; for the magnification value used in the example, this upper limit is approximately 50 microns.
If the problem of location error could be obviated, for maximum measurement speed and maximum parameter measurement range it is desirable that parameter distributions can be measured using the smallest possible number of pixels in the image of the smallest particle to be included in the characterization of the population.
It is an object of this invention, to provide a relatively fast and inexpensive system whereby a small number of pixels can be used to image a particle without significantly suffering from the effects of the location error normally associated with using a small number of pixels.